thinking-lindy-effect

The Lindy Effect

Overview

The Lindy Effect, named after a New York deli where comedians discussed career longevity, states that for non-perishable things (ideas, technologies, books, practices), future life expectancy is proportional to current age. If a technology has survived 20 years, it's likely to survive another 20. If it's survived 2 years, expect another 2.

Core Principle: Time is the ultimate test. Old things that still exist have proven their value; new things are still being tested.

When to Use

• Technology selection (languages, frameworks, databases)
• Evaluating libraries and dependencies
• Predicting tool longevity
• Career skill investment
• Methodology and practice adoption
• Architectural patterns
• Vendor/product selection

Decision flow:

Choosing between options?
  → Are some options significantly older? → yes → APPLY LINDY HEURISTIC
  → Is longevity important for this choice? → yes → FAVOR OLDER, PROVEN OPTIONS
  → Is the new thing solving a new problem? → yes → NEW MIGHT BE APPROPRIATE

When NOT to Use

• Not for perishable things — specific SaaS vendors, individual products, hardware, fashion-driven choices. Age predicts survival only for non-perishable ideas/technologies/practices.
• Not when a paradigm shift is underway. Lindy holds within a stable paradigm; a discontinuity (cloud, LLMs) can make the old thing's age irrelevant. If the ground is moving, age is not evidence.
• Not as a tiebreaker for short-lived/experimental work where longevity doesn't matter — pick on fit, not age.
• Don't read Lindy as "old = best." Survival predicts further survival; it does not say the old option is optimal for a new requirement. The burden of proof is on the new — but the new can meet it.

Trigger Card

When choosing a technology, framework, or dependency and longevity matters:

1. Check the age — how long has this option survived? For non-perishable things (ideas, technologies, institutions), expected remaining life is proportional to current age.
2. Verify it's non-perishable — is the option subject to rapid obsolescence (JS framework) or cumulative knowledge (database, language, protocol)? Lindy only applies to the latter.
3. Favor the proven over the new — let the new option carry the burden of proof. Pick the older option unless the new one demonstrates a clear, necessary advantage.

Skip for short-lived/experimental work where longevity doesn't matter. "Old" isn't automatically "best" — survival predicts further survival, not optimality for a new requirement.

Understanding Lindy

What Lindy Applies To (Non-Perishable)

• Technologies: Languages, databases, protocols
• Ideas: Mathematical concepts, design patterns, algorithms
• Practices: Testing, version control, code review
• Books: Technical references, foundational texts
• Institutions: Standards bodies, open source foundations

What Lindy Doesn't Apply To (Perishable)

• Hardware: Physical degradation limits life
• Individual careers: Humans have biological limits
• Specific products: Companies can fail, be acquired
• Fashion-driven choices: Popularity cycles aren't Lindy

The Math

Expected remaining life ≈ Current age

If survived 10 years → Expected to survive another ~10
If survived 50 years → Expected to survive another ~50
If survived 2 years → Expected to survive another ~2

Applying Lindy to Technology

Programming Languages

Language	Age	Lindy Expectation	Evidence
C	50+ years	50+ more years	Powers OS, embedded, will outlive us
Java	30 years	30+ more years	Enterprise backbone, not going away
Python	30 years	30+ more years	Scientific computing, ML, scripting
Go	15 years	15+ more years	Proven for infra, backed by Google
Rust	10 years	10+ more years	Growing, solving real problems
New hotness	2 years	2-5 years	Unproven, might disappear

Databases

Database	Age	Lindy Expectation	Notes
PostgreSQL	35+ years	35+ more years	SQL is 50+ years old
MySQL	30 years	30+ more years	LAMP stack foundation
MongoDB	15 years	15+ more years	Survived NoSQL hype cycle
CockroachDB	10 years	10+ more years	NewSQL, still proving itself
Latest DB	2 years	Unknown	High risk for production use

Frameworks

Framework	Age	Lindy Expectation	Notes
React	10+ years	10+ more years	Dominant, ecosystem mature
Rails	20 years	20+ more years	Productive, battle-tested
Django	18 years	18+ more years	Python's Rails, stable
Express	14 years	14+ more years	Node.js standard
Newest framework	1 year	1-3 years	Likely to be replaced

Patterns and Practices

Practice	Age	Lindy Expectation
Version control	50+ years	Permanent
Automated testing	40+ years	Permanent
Code review	40+ years	Permanent
Agile (core ideas)	30+ years	Very long
CI/CD	20+ years	Very long
Microservices	10 years	Moderate
Latest methodology	2 years	Unknown

The Lindy Decision Process

Step 1: Assess Age of Options

For each option, determine how long it's been in significant use:

Options for message queue:
- RabbitMQ: 17 years (2007)
- Kafka: 13 years (2011)
- NATS: 11 years (2013)
- NewQueue: 2 years (2022)

Step 2: Apply Lindy Heuristic

Lindy expectation:
- RabbitMQ: 17+ more years
- Kafka: 13+ more years
- NATS: 11+ more years
- NewQueue: 2-5 more years (high uncertainty)

Step 3: Consider Context

Lindy is a heuristic, not a law. Consider:

When older is better:
- Long-term production systems
- Core infrastructure
- Skills investment
- Dependencies with many consumers

When newer might be appropriate:
- Solving genuinely new problems
- Performance-critical new workloads
- Specific capability older tools lack
- Temporary/experimental projects

Step 4: Calibrate by Ecosystem Age

A 5-year-old tool in a 5-year-old ecosystem is "old" for that ecosystem:

Kubernetes ecosystem: ~10 years old
- Helm: 8 years → "Lindy" for K8s
- ArgoCD: 7 years → "Lindy" for K8s
- New tool: 1 year → Not Lindy yet

Node.js ecosystem: 14 years old
- Express: 14 years → Maximally Lindy for Node
- Fastify: 8 years → Moderately Lindy
- New framework: 1 year → Unproven

Lindy Failure Modes

Survivor Bias Confusion

Lindy predicts future survival given current survival. It doesn't say all old things are good:

Correct: "COBOL has survived 60 years, will survive 60 more"
Incorrect: "COBOL is the best choice for new projects"
(Survival ≠ Optimal for new use cases)

Ignoring Paradigm Shifts

Lindy works within stable paradigms. Paradigm shifts create discontinuities:

- Pre-cloud: On-premise databases were Lindy
- Post-cloud: Managed databases emerged
- But: Core database concepts (SQL, ACID) remained Lindy

Confusing Perishable and Non-Perishable

Perishable: Specific SaaS vendor → Can be acquired, pivoted, shut down
Non-perishable: The practice the vendor enables → Likely Lindy

E.g., Heroku might change, but "platform-as-a-service" concept is Lindy

Lindy in Practice

Technology Selection

## Lindy Analysis: Database for New Product

Requirements: ACID transactions, relational data, long-term stability

Options:
| Option | Age | Lindy Score | Fit for Requirements |
|--------|-----|-------------|---------------------|
| PostgreSQL | 35 years | Excellent | Excellent |
| MySQL | 30 years | Excellent | Good |
| CockroachDB | 10 years | Good | Excellent |
| PlanetScale | 5 years | Moderate | Good |

Decision: PostgreSQL (Lindy + excellent fit)
         Consider CockroachDB for scale needs (worth the Lindy tax)

Skill Investment

## Lindy Career Analysis

Which skills to invest in?

Lindy skills (high confidence in future value):
- SQL (50+ years)
- Unix/Linux (50+ years)
- Git/version control (40+ years)
- Testing fundamentals (40+ years)

Moderate Lindy (good bet):
- Python (30+ years)
- JavaScript (28 years)
- Docker/containers (12 years)
- Kubernetes (10 years)

Low Lindy (speculative):
- Latest framework (1-3 years)
- Trending language (variable)

Investment strategy: Core in Lindy skills, experiments in new

Dependency Selection

## Lindy Dependency Audit

For each critical dependency:
| Dependency | Age | Last Update | Contributors | Lindy Risk |
|------------|-----|-------------|--------------|------------|
| lodash | 12 years | Active | Many | Low |
| express | 14 years | Active | Many | Low |
| new-lib | 1 year | Active | 3 | High |

Policy: Critical path requires 5+ year Lindy
        Experimental features can use newer dependencies

Lindy Template

# Lindy Analysis: [Decision]

## Options with Age
| Option | First Stable | Age | Category |
|--------|--------------|-----|----------|
| | | | Proven/Moderate/New |

## Lindy Expectations
| Option | Expected Longevity | Confidence |
|--------|-------------------|------------|
| | | High/Medium/Low |

## Context Adjustments
- Is this a new problem domain? [Yes/No]
- Is the ecosystem mature? [Yes/No]
- Do newer options solve critical gaps? [Yes/No]

## Lindy-Adjusted Decision
Primary choice: [Option with best Lindy + fit]
Rationale: [Why this balances Lindy with requirements]

## Risk if Lindy is Wrong
[What happens if the non-Lindy option outlasts expectations?]

Verification Checklist

• Identified age of all options
• Applied Lindy heuristic to estimate longevity
• Distinguished perishable from non-perishable
• Considered paradigm shift possibilities
• Checked if newer options solve genuinely new problems
• Balanced Lindy with specific requirements
• Documented reasoning

Key Questions

• "How long has this technology/practice existed?"
• "Is this Lindy (non-perishable) or perishable?"
• "What's the Lindy expectation for each option?"
• "Is the newer option solving a problem that didn't exist before?"
• "Am I betting against Lindy? If so, why?"
• "What's proven vs. what's hyped?"

Taleb's Wisdom

"If a book has been in print for forty years, I can expect it to be in print for another forty years. But, and that is the main difference, if it survives another decade, then it will be expected to be in print another fifty years."

"Technology is at its best when it is invisible."

The technologies you don't think about—TCP/IP, Unix, SQL—are the most Lindy. The technologies that demand constant attention are still being tested.

"The old is to be respected; the new is to be examined."

Lindy doesn't mean reject the new. It means: the burden of proof is on the new. New must demonstrate value; old has already demonstrated survival.